Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.


We utilise our cutting-edge, exclusive workflow to develop focused libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q6ZVT0

UPID:
TTL10_HUMAN

ALTERNATIVE NAMES:
Tubulin--tyrosine ligase-like protein 10

ALTERNATIVE UPACC:
Q6ZVT0; B1AMF6; Q5T2W4; Q5T2W5; Q8N9X2

BACKGROUND:
The protein Inactive polyglycylase TTLL10, alternatively known as Tubulin--tyrosine ligase-like protein 10, is distinguished by its unique enzymatic classification. With the UniProt accession Q6ZVT0, it contributes to the intricate landscape of protein function and regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Inactive polyglycylase TTLL10 offers promising pathways for therapeutic intervention. The protein's unique characteristics and roles in cellular processes highlight its potential as a target in the development of novel treatment strategies.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.